Adaptation Space

Adaptation space, the set of options available for a self-adaptive system to respond to changing conditions, is a crucial area of research focusing on efficiently managing and navigating this space. Current research emphasizes using machine learning, particularly deep learning models, to reduce the computational burden of analyzing large adaptation spaces and to handle the "drift" of these spaces over time, where the optimal options change due to unforeseen circumstances. This work aims to improve the effectiveness and efficiency of self-adaptive systems across various applications, particularly in domains like the Internet of Things, by enabling more robust and responsive systems that can adapt to dynamic environments.